Lessons learned from the COVID-19 pandemic: The importance of physician leadership in responding to rural community ecosystem disruptions
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic presented an unprecedented challenge for rural family physicians. The lessons learned over the course of 2 years have potential to help guide responses to future ecosystem disruption. This qualitative study aims to explore the leadership experiences of rural Canadian family physicians during the COVID-19 pandemic as both local care providers and community health leaders and to identify potential supports and barriers to physician leadership. METHODS: Semi-structured, virtual, qualitative interviews were completed with participants from rural communities in Canada from December 2021 to February 2022 inclusive. Participant recruitment involved identifying seed contacts and conducting snowball sampling. Participants were asked about their experiences during the COVID-19 pandemic, including the role of physician leadership in building community resilience. Data collection was completed on theoretical saturation. Data were thematically analysed using NVivo 12. RESULTS: Sixty-four participants took part from 22 rural communities in 4 provinces. Four key factors were identified that supported physician leadership towards rural resilience during ecosystem disruption: (1) continuity of care, (2) team-based care models, (3) physician well-being and (4) openness to innovative care models. CONCLUSION: Healthcare policy and practice transformation should prioritise developing opportunities to strengthen physician leadership, particularly in rural areas that will be adversely affected by ecosystem disruption. INTRODUCTION: La pandémie de COVID-19 a représenté un défi sans précédent pour les médecins de famille en milieu rural. Les leçons tirées au cours des deux années écoulées peuvent aider à orienter les réponses aux futures perturbations de l'écosystème. Cette étude qualitative vise à explorer les expériences de leadership des médecins de famille ruraux canadiens pendant la pandémie de COVID-19, en tant que prestataires de soins locaux et chefs de file de la santé communautaire, et à identifier les soutiens et les obstacles potentiels au leadership des médecins. MTHODES: Des entretiens qualitatifs virtuels semi-structurés ont été réalisés avec des participants issus de communautés rurales du Canada entre décembre 2021 et février 2022 inclus. Le recrutement des participants a consisté à identifier des contacts de base et à procéder à un échantillonnage boule de neige. Les participants ont été interrogés sur leurs expériences durant la pandémie de COVID-19, notamment sur le rôle du leadership des médecins dans le renforcement de la résilience des communautés. La collecte des données s'est achevée après saturation théorique. Les données ont été analysées thématiquement à l'aide de NVivo 12. RSULTATS: Soixante-quatre participants provenant de 22 communautés rurales de quatre provinces ont pris part à l'étude. Quatre facteurs clés ont été identifiés pour soutenir le leadership des médecins en faveur de la résilience rurale en cas de perturbation de l'écosystème: (1) la continuité des soins, (2) les modèles de soins en équipe, (3) le bien-être des médecins et (4) l'ouverture à des modèles de soins novateurs. CONCLUSION: La politique de santé et la transformation des pratiques devraient donner la priorité au développement d'opportunités pour renforcer le leadership des médecins, en particulier dans les zones rurales qui seront négativement affectées par la perturbation de l'écosystème.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".